Glossary
Governance Framework
A structured set of policies, processes, and controls for managing AI agent development, deployment, and operation within an organization.
What is Governance Framework?
Governance frameworks define how organizations make decisions about AI agents, allocate responsibilities, manage risks, and ensure compliance. Key elements include risk assessment processes, approval workflows for agent deployment, monitoring requirements, incident response procedures, and accountability structures. Effective governance balances enabling innovation with managing risks and meeting regulatory requirements.
Frameworks typically assign roles like AI ethics boards, model risk management teams, and agent owners with specific responsibilities. They define standards for documentation, testing, security controls, and ongoing monitoring. Strong governance includes regular reviews, audit rights, and mechanisms for updating policies as AI capabilities and risks evolve. Industry-specific frameworks address sector regulations like financial services or healthcare requirements.
Example
A bank's AI governance framework requires all customer-facing agents to undergo model risk review, receive ethics board approval, complete security testing, document training data sources, implement human oversight for high-value decisions, and submit quarterly performance reports to compliance.
How Signet addresses this
Signet's Security dimension evaluates governance maturity, with agents operating under documented frameworks scoring higher. The framework demonstrates organizational commitment to responsible AI operation. Governance quality affects trust scores across multiple dimensions.
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